Developing mRNA signatures as a novel prognostic biomarker predicting high risk multiple myeloma.

ABSTRACT:

Background

Multiple myeloma (MM) remains an essentially incurable disease. This study aimed to establish a predictive model for estimating prognosis in newly diagnosed MM based on gene expression profiles.

Methods

RNA-seq data were downloaded from the Multiple Myeloma Research Foundation (MMRF) CoMMpass Study and the Genotype-Tissue Expression (GTEx) databases. Weighted gene coexpression network analysis (WGCNA) and protein-protein interaction network analysis were performed to identify hub genes. Enrichment analysis was also conducted. Patients were randomly split into training (70%) and validation (30%) datasets to build a prognostic scoring model based on the least absolute shrinkage and selection operator (LASSO). CIBERSORT was applied to estimate the proportion of 22 im

SUBMITTER: Wang J 

PROVIDER: S-EPMC9995860 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature